Erdem, Gamze
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Araş.Gör.
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01.01.09.03. Endüstri Mühendisliği Bölümü
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11
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17
Scholarly Output
9
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1
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2
Scopus Citation Count
7
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0.22
Scopus Citations per Publication
0.78
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1
| Journal | Count |
|---|---|
| 24th International Symposium for Production Research ISPR 2024 | 2 |
| 4th International Conference on Intelligent and Fuzzy Systems (INFUS) | 1 |
| 22nd International Symposium for Production Research ISPR 2022 | 1 |
| Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference | 1 |
| International Conference on Intelligent and Fuzzy Systems INFUS 2022 | 1 |
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9 results
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Conference Object Whale Optimization Algorithm for Job Scheduling Problem(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Gamze Erdem; Ege Duran; Paldrak, Mert; Duran, Ege; Erdem, Gamze; N.M. Durakbasa , M.G. GençyılmazMeta-heuristics are widely used methods in OR literature. Whale Optimization Algorithm (WOA) is one of these meta-heuristic methods which is recently developed. The objective of this study is to find the best possible job schedule while minimizing the make-span (i.e. the length of time elapsed from the beginning of first job to the end of the last job.) of the system. This problem is initially solved by using Optimization Programming Language namely CPLEX Studio IDE 20.1.0. Then WOA which is a current meta-heuristic used to solve the same problem. Some toy instances of different sizes are created and the results obtained by using CPLEX and WOA are compared. Although in some studies in the literature WOA is used to solve job shop scheduling problems there is not a study which uses WOA as a solution methodology for parallel machine job scheduling problem with machine eligibility consideration to the best of our knowledge. Thus the main contribution of this study is to include machine eligibility to the conventional job scheduling problem and to use WOA while solving the corresponding problem. © 2023 Elsevier B.V. All rights reserved.Conference Object The Facility Location Problem with Fuzzy Parameters(Springer Science and Business Media Deutschland GmbH, 2022) Gamze Erdem; Ayhan Özgür Toy; Adalet Oner; Toy, A. Özgür; Öner, Adalet; Erdem, Gamze; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. CebiThere is a variety of studies about Facility Location Problems (FLP) in Operations Research (OR) literature. The studies in the literature generally assume a deterministic environment. However studies relaxing the deterministic assumption are not rare. One way of incorporating uncertainties in these problems is through fuzzy parameters. While incorporating uncertainties into the problem Fuzzy set theory has some advantages over the other popular approach to handle uncertainties which is probabilistic theory. Unlike probabilistic theory the fuzzy set theory yields a logical manner to model uncertainties without the need for any historical data. Our focus in this work is to survey the collection of the recent publications on FLP with fuzzy parameters. Uncertain demands variable costs and travel durations as well as some subjective factors that are scaled in linguistic values can be given as examples for fuzzy parameters. As a methodology of this work firstly we start by listing parameters of the classical FLP and then present studies which consider these parameters as fuzzy sets and classify them accordingly. Secondly we group these studies based on the solution methodology implemented. Our search domain for the literature is primarily the Web of Science database. However we do not limit ourselves to that database in general. Our contribution is to provide knowledge about the properties of the fuzzy environments in facility location models. © 2022 Elsevier B.V. All rights reserved.Conference Object Resolving Stakeholder Conflicts in Airport Gate Assignment: A Multi-objective Approach with Goal Programming and MIP Models(Springer Science and Business Media Deutschland GmbH, 2025) Mert Paldrak; Gamze Erdem; Melis Tan Tacoglu; Mustafa Arslan Ornek; Paldrak, Mert; Örnek, Mustafa Arslan; Tacoğlu, Melis Tan; Erdem, Gamze; N.M. Durakbasa , K.G. GülenThe Airport Gate Assignment Problem (AGAP) is a critical aspect of airport operations involving the assignment of gates to incoming and outgoing flights. In this study we model the AGAP as a multi-objective optimization problem addressing the conflicting preferences of key stakeholders: passengers airlines and airport management. Each stakeholder has distinct gate preferences creating challenges in balancing their competing objectives. To address these challenges we develop Mixed Integer Programming (MIP) models incorporating both assignment-based and time-tabling-based approaches. The solution process leverages Goal Programming techniques including Weighted Goal Programming Tchebychev Goal Programming and Lexicographic Goal Programming. The models are implemented and solved using IBM ILOG CPLEX Version 12.0 providing a robust framework for optimizing gate assignments while considering the complex trade-offs between stakeholder preferences. Our results offer insights into the effectiveness of these techniques in resolving conflicts and achieving an optimal balance in gate assignments. © 2025 Elsevier B.V. All rights reserved.Conference Object Citation - WoS: 2Citation - Scopus: 5A Literature Review on Supplier Selection Problem and Fuzzy Logic(SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Mert Paldrak; Gamze Erdem; Melis Tan Tacoglu; Simge Guclukol; Efthimia Staiou; Tan Tacoğlu, Melis; Paldrak, Mert; Guclukol, Simge; Staiou, Efthimia; Tacoglu, Melis Tan; Erdem, Gamze; C Kahraman; AC Tolga; SC Onar; S Cebi; B Oztaysi; IU SariGiven the recent increasing competition in global market supplier selection and evaluation has attracted a great deal of attention especially at academic levels. Supplier selection problem is a complex problem since there exist a great number of unpredictable and uncontrollable factors which have a huge impact on decision-making process. Due to this complexity there are several criteria that must be taken into consideration such as cost quality on-time delivery proximity of suppliers long-term relationship etc. Although some of these criteria (quantitative) can be expressed using pure numeric scales some (qualitative) are linguistic due to the human assessments which contain some degree of subjectivity. Since involvement of human assessment causes vagueness for deterministic models the authors apply fuzzy logic which enables the decision makers to be able to convert their linguistic expressions into fuzzy numbers with the help of fuzzy membership functions. Considering that fuzzy logic plays a vital role in solving multi-criteria supplier selection problem this paper aims to present a review of supplier selection problem and its relation with fuzzy logic. In this paper several studies that highlight supplier selection problem and the importance of fuzzy logic involvement in the problem have been reviewed. An analysis of multi-criteria decision-making methods for supplier selection problem is conducted.Master Thesis Adil tek kaynaklı ve kapasiteli tesis lokasyonu problemi(2021) Erdem, Gamze; Öner, AdaletThis thesis concerns with the bi-objective Single-Source Capacitated Facility Location Problem. The first component of the objective function comprises of fixed opening cost of facilities and assignment costs of demand points to the facilities. The second component is related to the fairness of the assignments. The fairness objective is expressed in terms of the conditional β-mean concept. The characteristics of the problem are discussed and related mathematical models are given. Three solution methods; the Weighted Sum method, the Epsilon Constraint method, and the Benders Decomposition method are used to show the solutions of the problem. Benchmark problem instances are solved to test the solution methods. The outcomes are reported and solution methods are compared to each other. As outcomes of the study; the Epsilon Constraint Method is able to find a greater number of solutions than the Weighted Sum Method and the Benders Decomposition Method is found to perform better as the sizes of the problems increase.Conference Object Citation - Scopus: 2A Firefly Algorithm for Bi-Objective Airport Gate Assignment Problem(Springer Science and Business Media Deutschland GmbH, 2024) Mert Paldrak; Gamze Erdem; Mustafa Arslan Ornek; Paldrak, Mert; Örnek, Mustafa Arslan; Erdem, Gamze; N.M. Durakbasa , M.G. GençyılmazThe Airport Gate Assignment Problem (AGAP) is a challenging combinatorial optimization problem that arises in the efficient management of airport operations in daily basis. The task involves assigning arriving and departing aircrafts to appropriate gates within an airport terminal while maintaining safety and security of passengers along with various problem-specific constraints. Efficient gate assignment is of paramount importance for smooth airport operations since it directly affects such crucial factors as passenger flow aircraft turnover time gate utilization and overall airport capacity. The AGAP is rendered increasingly complex with factors such as multiple airlines varying aircraft sizes gate capacities maintenance requirements etc. In real life most hub-and-spoke airports have deals with numerous arriving and departing aircrafts and bridge-equipped gates. Consequently solving the AGAP requires tackling a complex combinatorial optimization task which cannot be solved using traditional optimization methods. In such cases metaheuristic algorithms have emerged as effective tools to address this NP-hard problem. In this study we employ a Firefly Optimization Algorithm to handle the AGAP in a reasonable amount of computational time. Firefly Optimization Algorithm is applied by formulating it as an optimization problem and aims to find an optimal gate assignment solution that maximizes total flight-to-gate assignment utility and minimizes numbers of flights assigned to apron. The algorithm is coded through MATLAB ® 2016 of a personal computer. The results obtained using Firefly Optimization Algorithm is compared to those solutions obtained through IBM ILOG CPLEX 12.0 Optimization Tool. © 2024 Elsevier B.V. All rights reserved.Conference Object Fuzzy Goal Programming Approach to Multi-objective Facility Location Problem for Emergency Goods and Services Distribution(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Simge Güçlükol Ergin; Gamze Erdem; Melis Tan Tacoglu; Paldrak, Mert; Tacoğlu, Melis Tan; Ergin, Simge Güçlükol; Erdem, Gamze; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. TolgaEnsuring the distribution of vital goods and services during emergency or post-disaster situations is crucial for meeting the needs of those affected as quickly as possible. The challenge lies in finding suitable and pertinent locations for facilities to efficiently distribute these goods and services. In such a situation location decisions for these facilities must be made considering multiple objectives. However in such a real-life problem the aspiration levels of each of the objectives are not certainly known due to unpredictable results of a disaster. Consequently the problem is formulated as fuzzy multi-objective facility location problem where two objectives are taken into consideration. We specifically consider minimization of total cost of facilities to be opened and minimization of total distance travelled by victims. Due to the conflicting nature of these objective functions we propose to employ two different fuzzy weighted goal programming techniques to find suitable compromise solutions for the problem. We present our developed models and provide results for three instances with different sizes. The proposed models are coded using IBM CPLEX Optimizer to obtain solutions in a reasonable amount of computational time. This paper contributes to the literature by providing two different fuzzy weighted goal programming techniques and comparing their efficiencies. © 2023 Elsevier B.V. All rights reserved.Conference Object Reinforcement Learning in Condition-Based Maintenance: A Survey(Springer Science and Business Media Deutschland GmbH, 2025) Gamze Erdem; Mehmet Cemali Dinçer; Mehmet Murat Fadiloglu; Dincer, M. Cemali; Fadiloglu, M. Murat; Erdem, Gamze; C. Kahraman , S. Cebi , B. Oztaysi , S. Cevik Onar , C. Tolga , I. Ucal Sari , I. OtayThis literature review examines the convergence of Reinforcement Learning (RL) and Condition-Based Maintenance (CBM) emphasizing the trans- formative impact of RL methodologies on maintenance decision-making in com- plex industrial settings. By integrating insights from a diverse array of studies the review critically assesses the use of various RL techniques such as Q-learning deep reinforcement learning and policy gradient approaches in forecasting equipment failures optimizing maintenance schedules and reducing operational downtime. It outlines the shift from conventional rule-based maintenance practices to adaptive data-driven strategies that exploit real-time sensor data and probabilistic modeling. Key challenges highlighted include computational complexity the extensive training data requirements and the integration of RL models into existing industrial frameworks. Furthermore the review explores literature on CBM within multi-component systems where prevalent approaches include numerical analyses Markov Decision Processes (MDPs) and case studies all of which demonstrate notable cost reductions and decreased downtime. Relevant studies were identified through searches on databases such as Google Scholar Scopus and Web of Science. Overall this review provides a comprehensive analysis of the current state and prospects of employing reinforcement learning in condition-based maintenance offering valuable insights for both academic researchers and industry practitioners. © 2025 Elsevier B.V. All rights reserved.Conference Object Mixed-Integer and Constraint Programming Approaches for Determination of Locations of Long-Term Care Facilities(Springer Science and Business Media Deutschland GmbH, 2025) Mert Paldrak; Gamze Erdem; Gökberk Ozsakalli; Armağan Yağız Terim; Özsakallı, Gökberk; Paldrak, Mert; Terim, Armaǧan Yaǧız; Erdem, Gamze; N.M. Durakbasa , K.G. GülenThis study addresses the Long-Term Care Facility Location Problem (LTCFLP) focusing on the optimal location of long-term care facilities in İzmir Turkiye. Long-term care facilities often referred to as nursing homes provide medical services and daily assistance to individuals primarily the elderly over extended periods. As the aging population increasing globally the demand for such facilities has grown prompting governments to invest in their development. This research aims to determine the best locations for these facilities balance the load across facilities and o minimize both the establishment and patient assignment costs. The problem is formulated as a multi-objective optimization model considering facility capacity overcapacity allowance and facility utilization. A mixed-integer programming model is developed to achieve these objectives. Additionally a novel contribution is made by applying a constraint programming (CP) approach which has not been used for LTCFLP before. The study compares the results from both mixed-integer programming (MIP) and constraint programming models to evaluate their efficiency and effectiveness in solving this complex real-world problem. The results highlight the trade-offs between different models and propose future research directions for enhancing facility location planning. © 2025 Elsevier B.V. All rights reserved.
